Sample selection

The probability of each case being selected from the population is known and equal for all cases. This allows for estimations about the population from sample data.

The probability of each case being selected from the population is unknown and statistical inferences about the populations characteristics are impossible.

Quantitative and involves selecting the sample at random fromt the sampling frame.

Quantitative and involves selecting the sample at regular intervals from the sampling frame.

Quantitative method by dividing the population into two or more relevant and significant strata based on one or a number of attributes.

Quantitative method where the population needs to be divided into discrete groups prior to sampling. The groups are termed clusters and can be based on any naturally occurring grouping.

A development of cluster sampling used to overcome geographically dispersed population when face-to-face contact is needed or it is expensive and time consuming to construct a sampling frame.

A development of cluster sampling used to overcome geographically dispersed population when face-to-face contact is needed or it is expensive and time consuming to construct a sampling frame.

Non-probability sampling and used for interview surveys. Assuming the sample will represent the population and its variability.

Non-probability sampling and used for interview surveys. Assuming the sample will represent the population and its variability.

Non-probability sampling where the researcher uses its judgement to select cases that will best enable to answers research questions and meet objectives.

Non-probability sampling used when it is difficult to identify members of the desired population. Participants volunteered to participate in the research,instead of being chosen by the researcher.

Non-probability sampling where individuals desire to participate in the research.

Non-probability sampling where one selects those cases that are easiest to obtain for the sample.